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What's your data worth?

Overview

As the volume and variety of data continues to rise, so do the opportunities to find value in it. But to identify data monetization opportus-driven mann

nities in an informed and result

er, companies must assess the value of enterprise data, determine how best to maximize its potential and figure out how to get the data to the market efficiently.

Data capture and analysis technologies and techniques can help companies to maximize the potential of their data. But the first step is to address two key questions:

Does the company have valuable data?

What is the right business model to extract that value?

Taking a pragmatic approach to answering these questions will help companies accelerate the journey to data monetization.

Creating Revenue from Customer Data: A Data Monetization Framework

Background

Big data just keeps getting bigger. Over the past decade, companies have seen exponential growth in volume, variety and speed of data. It can be overwhelming, but it can also be eye-opening as more companies are becoming aware of the opportunities embedded in their enterprise data. However, few have developed active strategies for successful data monetization.

Such a strategy requires companies to not only understand the quality of their data, but also to build a strategy and an appropriate business model for selling the data to other companies.

Analysis
A number of forces have converged to create the right conditions for data monetization. Not only is the cost of storing data steadily decreasing, but the ability to process and analyze big data in real time is increasing.

Companies are using analytics and business intelligence tools to create data monetization opportunities by leveraging all their data assets, structured and unstructured, within enterprise systems. For example:

Retailers are using big data infrastructure to automate the process of analyzing billions of transactions.

Financial services companies are using analytics and business intelligence tools to analyze thousands of trades in a fraction of a second to be able to capture profit from minor market inefficiencies.

Key Findings

Companies can evaluate their data monetization opportunities in a more informed and results-driven way by assessing the value of enterprise data, determining how best to maximize its potential and figuring out how to get the data to the market efficiently.

Getting to the data value
Data is the foundation of the data monetization strategy, but to understand its value, companies must assess key criteria, including:

Consumer behavior

Consumer identification

Transaction identification

Unique data

Accessible data

Finding the market opportunity
The Accenture Data Monetization Framework outlines five key stages to help companies commercialize their enterprise data. At each stage of the data value chain, enterprise data becomes more refined, relevant and valuable to the company. These stages include:

Raw data

Processed data

Insights

Presentation

Transact

Go to market approach
As companies shape new data-driven business ventures and look to move up the data value chain, they need to determine how they will commercialize a particular data strategy. Areas to consider include:

Perceived value of the market

Privacy concerns

Evaluation of core competency

Agile organization

Cross-industry alliances

Read the full article to learn more about each of these critical steps.

RECOMMENDATIONS

Big data infrastructure and technologies are driving down the costs of executing data monetization strategies. The data monetization opportunity is ripe for any company that gathers data on the use of its goods and services, particularly consumer data.

But before embarking on the journey, companies must take the time to understand the potential value embedded in enterprise data, and where on the value chain the company wants to position the new data-driven business. With the right business model and strategic alliances, companies can unleash potential revenue streams from data monetization.

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